For those not familiar with MATLAB, it is the definitive math software, great for matrix manipulation, used throughout college and graduate school labs. Solid software for any one pursuing a PhD in quantitate fields and advanced social science studies. Had to use MATLAB for my work at a Stanford Physics lab a long long time ago and also a few Physics PhDs still use it. You can get a student discount (very substantial, lifetime license) from most US universities.

After releasing Course 1 of the Deep Learning specialization on Coursera, Andrew Ng's team is working on releasing the next few courses: Course 2, 3, 4 Convolutional Neural Network (Late October) and 5. Sequence Models (Late November). Course 1-3 are available right now on Coursera.

For those new to the realm of Machine Learning, you will need CNN to do machine learning work on images. Sequence models are used for Natural Langue Processing and Audio models, pretty advanced.

My personal experience with the series so far: knowledgeable, info packed, still Andrew Ng talking one man team one man class, great sequel to his Machine Learning course, and the Udacity Machine Learning Engineering Nanodegree, but definitely need some background on ML techniques and NN.

Ask me about this course, ask me about the Udacity machine learning engineering nanodegree. I have quite some in-depth experience with the two.

"Since 2010, ImageNet has hosted an annual challenge where research teams present solutions to image classification and other tasks by training on the ImageNet dataset. ImageNet currently has millions of labeled images; it’s one of the largest high-quality image datasets in the world. The Visual Geometry group at the University of Oxford did really well in 2014 with two network architectures: VGG-16, a 16-layer convolutional Neural Network, and VGG-19, a 19-layer Convolutional Neural Network."

Imagenet can output 1000+ classes. If we don't need that many, instead need transfer learning should consider replacing it with bottleneck of only 1-10 classes.

Youtube 8M Video Data Kaggle https://www.kaggle.com/c/youtube8m

1000+ different objects in 1.3 million high resolution training images

“Twenty Newsgroups” The 20 Newsgroups data set is a collection of approximately 20,000 newsgroup documents, partitioned (nearly) evenly across 20 different newsgroups. To the best of our knowledge, it was originally collected by Ken Lang, probably for his paper “Newsweeder: Learning to filter netnews,” though he does not explicitly mention this collection. The 20 newsgroups collection has become a popular data set for experiments in text applications of machine learning techniques, such as text classification and text clustering.

As seen in this Michigan Data Science MOOC, Coursera now allows you to open and edit Jupyter Notebook right in the browser. Pretty amazing engineer! Truly the future of learning. Think of it as a super Codecademy.com

Saturday, October 7, 2017

Leonardo Da Vinci carefully studied the human anatomy of smiles and experimented with new painting techniques to create life like realistic smile of Mona Lisa. The smile is so illusive that it only is picked up by peripheral vision.